TBA
- Series
- School of Mathematics Colloquium
- Time
- Thursday, December 3, 2026 - 11:00 for 1 hour (actually 50 minutes)
- Location
- Skiles 005
- Speaker
- Thaleia Zariphopoulou – UT Austin
Contact geometry has a long history, with connections to many areas of physics and mathematics. I will begin with some history and motivation for contact geometry. I will then discuss the development of contact geometry in dimension three, and the central role knot theory has played in that development. We will end by considering the beautiful structure of special knots in contact manifolds and their use in classifying contact structures on three-manifolds.
Coupled oscillators appear in a large number of applications: e.g. in biological, chemical sciences, neuro science, power grids, and many more fields. They appear in nature: fireflies flashing in sync with each other is one fun situation.
In 1974, Yoshiki Kuramoto proposed a simple, yet surprisingly effective model for oscillators. We consider homogeneous Kuramoto systems (we will define these notions!). They are determined from a finite graph. In this talk, we describe some of what is known about long term behavior of such systems (do the oscillators self-synchronize? or are there other, "exotic" solutions?), and then relate these systems to systems of polynomial equations. We use algebra, computations in algebraic geometry, and algebraic geometry to study equilibrium solutions to these systems. We will see how computations using algebraic geometry and my computer algebra system Macaulay2 finds all graphs with at most 8 vertices (i.e. 8 oscillators) which have exotic solutions.
Note: we assume essentially NO dynamical systems nor algebraic geometry in this talk! This talk should be understandable to a general mathematical audience. The parts of the talk that are new represent joint work with Heather Harrington and Hal Schenck, and also Steve Strogatz and Alex Townsend.
In many applications of mathematical optimization, one may wish to optimize an objective function without access to its derivatives. These situations call for derivative-free optimization (DFO) methods. Among the most successful approaches in practice are model-based trust-region methods, such as those pioneered by M.J.D Powell. These methods rely on function approximations via low degree polynomials and carefully adapt the local geometry of interpolation points to balance exploration and exploitation. While relatively complex to implement, these methods are now available in standard scientific computing platforms, including MATLAB and SciPy. However, theoretical analysis of their computational complexity lags behind practice. In particular, it is important to bound the number of function evaluations required to achieve a desired level of accuracy. Using concepts from Lagrangian interpolation and linear algebra we systematically derive complexity bounds for classical model-based trust-region methods and their modern variations. We establish, for the first time, that these methods can have the same worst case complexity than any other known DFO method.
The spectrum of the discrete Laplacian on a infinite graph, or of its random perturbations such as the Anderson tight-binding model, encodes a rich information about the structure of that space. While natural questions abound (nature of the spectrum, localization of eigenfunctions, behavior of the spectral measure), few admit complete answers outside of very specific cases. In this talk, we will briefly survey some of the main open questions in the area. We will then present an elementary geometric criterion that provides control over the regularity of the spectral measure.
The Birkhoff Ergodic Theorem describes typical behaviors and averaged quantities with respect to an invariant measure. In this talk, I will focus on "observable" events, equating observability with positive Lebesgue measure. From this observational viewpoint, "typical" means typical with respect to Lebesgue measure. This leads immediately to issues for attractors, where all invariant measures are singular. I will present highlights of developments in smooth ergodic theory that address these questions. The theory of physical and SRB measures applies to dynamical systems that are deterministic as well as random, in finite and infinite dimensions (where observability has to be interpreted differently). This body of ideas argue in favor of convergence of ergodic averages for typical orbits. But the picture is a little more complicated: In the last part of the talk, I will discuss some recent work that shows that in many natural settings (e.g. reaction networks), it is also typical for ergodic averages
to fluctuate in perpetuity due to heteroclinic-like behavior.